Merat also discusses the challenges of AI, including the risk of perpetuating biases if trained on biased data. He suggests using deterministic AI models that analyze specific, case-by-case facts, rather than predictive models that rely on historical data patterns. He envisions a future where AI and human adjusters collaborate, with AI managing repetitive tasks and adjusters focusing on empathetic service. This, he believes, will improve the quality of care claimants receive and transform the insurance industry.
Key takeaways:
- The insurance industry has become more transactional and less human, often lacking empathy in the claims-settlement process, leading to a loss of trust among claimants.
- Artificial Intelligence (AI) has the potential to play a significant role in the insurance industry, not to replace humans but to bring humanity back to insurance by handling data-intensive tasks and reducing human bias in decision-making.
- AI can analyze millions of pages of complex claims records quickly, provide easy-to-understand summaries, detect potentially fraudulent claims, and reduce claimants' wait times, allowing human adjusters to focus on providing empathetic service.
- Despite the benefits of AI, it's important to use AI for deterministic tasks rather than predictive models to avoid perpetuating biases. Insurance carriers that adopt responsibly designed AI will be better positioned to improve the claims process, reduce bias, and extend more empathy to customers.